Projects  Research  Development  Innovation The contribution of our lab to science and technology can be divided into the following:
Computational intelligence combines elements of learning, adaptation, evolution and Fuzzy logic (fuzzy sets) to create programs that are, in some sense, intelligent. Computational intelligence research does not reject statistical methods, but often gives a complementary view (as is the case with fuzzy systems). Artificial neural networks is a branch of computational intelligence that is closely related to machine learning. Computational intelligence is further closely associated with soft computing, connectionist systems and cybernetics.
Soft Computing became a formal Computer Science area of study in the early 1990′s. Earlier computational approaches could model and precisely analyze only relatively simple systems. More complex systems arising in biology, medicine, the humanities, management sciences, and similar fields often remained intractable to conventional mathematical and analytical methods. That said, it should be pointed out that simplicity and complexity of systems are relative, and many conventional mathematical models have been both challenging and very productive. Soft computing deals with imprecision, uncertainty, partial truth, and approximation to achieve tractability, robustness and low solution cost. Components of soft computing include:
Researchers who collaborate with our projects:
